Future biofuel production opportunities in Sweden can be analysed in various ways. The BeWhere Sweden project series has had three different starting points, all with the aim of adding to the knowledge of aspects on optimal localisation of biofuel production through the use of an spatially explicit energy system model. Now, the third project within the series, BeWhere – Stake-holder analysis of biofuel production in Sweden, has delivered its final report.
The project has been carried out within the Swedish Energy Agency and f3 collaborative research program Renewable transportation fuels and systems and has been led by Elisabeth Wetterlund, Bio4Energy/LTU. Other project participants are SLU, Linköping University, RISE (formerly SP and Innventia), Lund University, Fortum, E.ON, Perstorp and SEKAB.
The study has investigated the usefulness of BeWhere Sweden for relevant actors and stakeholders in the biofuel area through model development and model runs based on actor dialogues, interviews, and workshops with actors representing potential users of the model and/or results from it.
Results showed that there are several ways to reach high levels of biofuel production in Sweden at reasonable costs, and that the dependency on specific locations or technologies is not particularly strong. Economy-of-scale and high conversion efficiencies were shown to provide the largest production cost reductions, which benefitted large-scale production of gasification based biofuels for use as high-blend or pure fuels.
Model result presentations must however be complemented with interpretations, and in order to use the results from models as a basis for decision-making, it is essential to understand the assumptions that have been integrated in the model. Also, aspects that are not easily included in this type of parameterised energy system model, such as social, political and (perceived) risk related factors, need to be considered since they were identified as critical barriers.
Overall, the conclusion is that BeWhere Sweden has the potential to be a useful part of a larger toolbox in the transformation towards forest-based biofuel production. A number of lessons have been learned, and both strengths and shortcomings of the model have been identified. The main strengths of the model lie in the spatial representation, and in the possibility to model different value chain options in detail, potentially identifying regional “hot-spots” for new production that can be used to create knowledge about factors affecting the costs and environmental impacts from biomass based supply chains. In turn, this can aid in the design of robust policies in order to facilitate effective development.
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