Modelling of integrative technology solutions for lignocellulosic biorefining

该项目将建立在一些初步研究的基础上，并采用系统工程建模方法，将生物炼制过程设计和供应链规划联系起来，寻求从木质纤维素生物质中进行增值生化回收的技术集成系统解决方案。这可以通过开发模拟-优化-评估建模方法来实现。过程设计和模拟技术将用于探索替代生物精炼途径；综合技术设计将通过应用生命周期分析和数学优化来进一步评估和优化系统性能目标，并突出技术改进机会，以实现经济效率和环境可持续性之间的权衡。随后，开发的模型可以应用于国际案例研究，例如中国的中粮集团，其中存在采用木质纤维素原料（主要是农业残留物）联合生产生物乙醇和增值生物产品的愿望。因此，这种原料的根本转变涉及到上述子系统作为所有尺度的过程和决定的仔细考虑和综合；从涉及的微观生化过程到国家规模，供应链和社会经济因素都受到影响。这项工作将作为生物可再生系统优化合作研究的一部分进行开发。该研究将建立在实验数据和试点/工业规模操作数据的基础上，与我们的学术和工业伙伴合作，以测试建模方法。

This project will build on some preliminary research and adopt a systems engineering modelling approach to bridge biorefinery process design and supply chain planning to seek technology integration system solutions for value-added biochemical recovery from lignocellulosic biomass. This can be achieved by developing a simulation-optimisation-evaluation modelling approach. The process design and simulation techniques will be deployed to explore alternative biorefining pathways; the integrative technology design will be further evaluated and optimised by applying Life Cycle Analysis and mathematical optimisation to set the system performance targets and highlight the technology improvement opportunities to achieve the trade-off between economic efficiency and environmental sustainability. Sequentially, the developed model can then be applied to international case studies, such as that of China's COFCO, in which there exists a desire to adopt lignocellulosic feedstock (primarily agro-residues) for the co-production of bioethanol and value-added bioproducts. Such a fundamental shift in feedstock, therefore, concerns the careful consideration and integration of the aforementioned sub-systems, as processes and decisions on all scales; from the micro-scale biochemical processes involved, to the national-scale, supply-chain and socio-economic considerations are affected. This work will be developed as the part of a biorenewable system optimisation collaboration research. The study will be built on the experimental data and pilot/industrial scale operational data in collaboration with our academic and industrial partners to test modelling methods.