Biomass supply chain optimisation for Organosolv-based biorefineries.

Area of Science:

• Industrial Biotechnology
• Process Systems Engineering
• Sustainable Energy Systems

Background:

• Biorefineries are crucial for sustainable chemical and energy production.
• Optimizing biorefinery economics and supply chains is essential for their viability.
• Existing models may lack the flexibility to address diverse biomass feedstocks and scales.

Purpose of the Study:

• To develop a Mixed Integer Linear Programming (MILP) modelling framework for sustainable biorefinery planning.
• To optimize the overall system economics for up-scaling an Organosolv biorefinery.
• To demonstrate the tool's applicability to various biomass types and supply strategies.

Main Methods:

• Development of a flexible MILP modelling framework.
• Optimization of biorefinery system economics.
• Case studies using forest fellings, cereal residues, and energy crops.

Main Results:

• The MILP framework effectively models different biomass typologies and supply strategies.
• Supply chain optimization is key to developing cost-efficient and sustainable biorefineries.
• Feedstock characteristics (quality, quantity, availability) significantly influence biorefinery location and supply costs.

Conclusions:

• The developed MILP framework provides a valuable tool for strategic biorefinery planning.
• Feedstock logistics and storage costs are critical economic factors in biorefinery design.
• Understanding supply chain dynamics is paramount for successful biorefinery implementation.