Abstract
Chemical manufacturing, transportation fuels production and power plants among other sectors have strongly depended on fossil-based resources. To support sustained economic growth, additional fossil-based resources are required, but, inevitably, this also has a major impact on the global environment. These challenges motivate thedevelopment of sustainable technologies for processing renewable feedstock for the production of fuels, chemicals and materials in what is commonly known as a biorefinery. The biorefinery concept is a term to describe one or more processes whichproduce various products from bio-based feedstock. Since there are several bio-basedfeedstock sources, this has motivated development of different conversion concepts producing various desired products. This results in a number of challenges for the synthesis and design of the optimal biorefinery concept at the early-stage of process development: (i) Combinatorial challenge: a large number of potential processing paths resulting from the combination of many potential feedstocks, and many available conversion technologies to produce a number of desired products; (ii) Data challenge: the data typically used for early stage process feasibility analysis is of a multidisciplinary nature, often limited and uncertain; (iii) Complexity challenge: this problem is complex requiring multi-criteria evaluation (technical, economic,sustainability). This PhD project aims to develop a decision support tool for identifying optimal biorefinery concepts at the early-stage of product-process development. To this end, asystematic framework has been developed, including a superstructure-based optimization approach, a comprehensive database of processing and conversion technologies, and model libraries to allow generation and comparison of a large numberof alternatives at their optimality. The result is the identification of the optimal rawmaterial, the product (single vs multi) portfolio and the corresponding process technology selection for a given market scenario. The economic risk of investment due to market uncertainties is further analysed to enable risk-aware decision making. Theapplication of the developed analysis and decision support toolbox is highlightedthrough relevant biorefinery case studies: bioethanol, biogasoline or biodiesel production; algal biorefinery; and bioethanol-upgrading concepts are presented. This development and analysis provides a robust guidance to support the development ofsustainable and future biorefineries.
Info
Thesis PhD, 2015
UN SDG Classification
DK Main Research Area
Science/Technology
