A. De Meyer, S. Verdonck, I. Storms, J. Lopez, M. Tschulkow, T. Compernolle, S. Van Passel, J. Van Orshoven, B. Verbist, R. Guisson, W. Arts, S. Van den Bosch, J. Van Aelst, B. Sels, and B. Muys (2024)
Spatio-temporal feedstock availability and techno-economic constraints in the design and optimization of supply chains: The case of domestic woody biomass for biorefining
Journal of Cleaner Production, 440(140873).
A future bio-based economy envisions the transformation of the petrochemical industry into using biomass such
as wood (waste) as a major resource. The early-stage evaluation of a biorefinery project requires the optimization
of the lay-out of the supply chain considering the spatio-temporal variability of the availability of feedstock and
the techno-economical characteristics of the biorefinery process. Therefore, the presented methodology was
developed combining three models: (1) a forest management and planning tool providing a detailed prediction
on the wood resource availability as well as the harvested feedstock quantity and cost with respect to location
and time, (2) a techno-economic assessment model of the biorefinery process (e.g., species-specific conditions,
capacity, CAPEX, OPEX), and (3) a strategic supply chain optimization model combining the insights of (1) and
(2) into a spatio-temporal explicit supply chain analysis.
The developed methodology has been evaluated through a case-study on the emerging reductive catalytic
fractionation (RCF) biorefining in the Flanders region (EU) and shows that the most economically interesting
configuration is one large biorefinery with a yearly wood chip intake of 150 kton. The biorefinery location reflects
the available feedstock distribution in Flanders and is suggested to be situated best in the most forested
region. The proposed methodology proved to be dynamic and robust: (1) input data and technical calculations
can easily be adapted or updated; (2) the methodology can be applied to a broad range of applications beyond
the scope of the biorefinery, to different feedstock choices; (3) the impact of the biorefinery location on e.g.
energy balance, CO2 emissions, and financial balance can be assessed.
Peer Review, Open Access, Impact Factor
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