Biomass supply chain optimisation for Organosolv-based biorefineries

Sara Giarola; Mayank Patel; Nilay Shah

doi:10.1016/j.biortech.2014.02.109

Biomass supply chain optimisation for Organosolv-based biorefineries

Bioresour Technol. 2014 May:159:387-96. doi: 10.1016/j.biortech.2014.02.109. Epub 2014 Mar 4.

Authors

Sara Giarola¹, Mayank Patel², Nilay Shah²

Affiliations

¹ CPSE, Centre for Process System Engineering, Chemical Engineering Department, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom. Electronic address: s.giarola10@imperial.ac.uk.
² CPSE, Centre for Process System Engineering, Chemical Engineering Department, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom.

PMID: 24675398
DOI: 10.1016/j.biortech.2014.02.109

Abstract

This work aims at providing a Mixed Integer Linear Programming modelling framework to help define planning strategies for the development of sustainable biorefineries. The up-scaling of an Organosolv biorefinery was addressed via optimisation of the whole system economics. Three real world case studies were addressed to show the high-level flexibility and wide applicability of the tool to model different biomass typologies (i.e. forest fellings, cereal residues and energy crops) and supply strategies. Model outcomes have revealed how supply chain optimisation techniques could help shed light on the development of sustainable biorefineries. Feedstock quality, quantity, temporal and geographical availability are crucial to determine biorefinery location and the cost-efficient way to supply the feedstock to the plant. Storage costs are relevant for biorefineries based on cereal stubble, while wood supply chains present dominant pretreatment operations costs.

Keywords: Biomass supply chain; Biorefinery; MILP; Optimisation; Organosolv process.

Publication types

Research Support, Non-U.S. Gov't
Retracted Publication