Bernhard Steubing
Swiss Federal Laboratories for Materials Science and Technology (Empa), Switzerland \ Swiss Federal Institute of Technology (EPFL), Switzerland
Isabel Ballmer
Swiss Federal Institute of Technology (ETHZ), Switzerland
Oliver Thees
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Switzerland
Léda Gerber
Swiss Federal Institute of Technology (EPFL), Switzerland
François Maréchal
Swiss Federal Institute of Technology (EPFL), Switzerland
Rainer Zah
Swiss Federal Laboratories for Materials Science and Technology (Empa), Switzerland
Christian Ludwig
Paul Scherrer Institute (PSI), Switzerland
Ladda ner artikelhttp://dx.doi.org/10.3384/ecp11057279Ingår i: World Renewable Energy Congress - Sweden; 8-13 May; 2011; Linköping; Sweden
Linköping Electronic Conference Proceedings 57:38, s. 279-286
Publicerad: 2011-11-03
ISBN: 978-91-7393-070-3
ISSN: 1650-3686 (tryckt), 1650-3740 (online)
Bioenergy from woodfuel has a considerable potential to substitute fossil fuels and alleviate global warming. One issue so far not systematically addressed is the question of the optimal size of bioenergy plants with regards to environmental and economic performance. The aim of this work is to fill this gap by modeling the entire production chain of wood and its conversion to bioenergy in a synthetic natural gas plant both with respect to economic and environmental performance. Several spatially explicit submodels for the availability; harvest; transportation and conversion of wood were built and joined in a multi-objective optimization model to determine optimal plant sizes for any desired weighting of environmental impacts and profits.
We find a trade-off between environmental and economic optimal plant sizes. While the economic optima range between 75 – 200 MW; the environmental optima are with 10 – 40 MW significantly smaller. Moreover; the economic optima are highly location specific and tend to be smaller if the biomass resource in the geographic region of the plant is scarcer. The results are similar with regards to the effect on global warming as well as with respect to the aggregated environmental impact assessment methods Ecoindicator ’99 and Ecological Scarcity 2006.
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