Ontwerp- en optimalisatiemethodologie voor kleinschalige bioraffinaderijen
Year: 2025
Type: dissertation
Abstract: Global initiatives like the European Green Deal and the Circular Economy Action Plan highlight the urgent need to optimise resource recovery from waste streams. In particular, biowaste holds untapped potential for conversion into valuable products. Converting these renewable feedstocks into usable products requires a series of bioconversion processes, i.e., a biorefinery. While centralised, large-scale biorefineries are already implemented on an industrial scale, their capital-intensive nature and strict feedstock requirements often render them unsuitable for areas with diverse land usage or agricultural output. Small-scale biorefineries, on the other hand, require smaller investments and can be tailored to the specific area in which they will be employed. If suitably designed and operated, these facilities can convert community-generated biowaste into high-value products, resulting in both environmental benefits and local economic gains. However, small-scale biorefineries remain underutilised, often owing to limited awareness of such waste-processing solutions by stakeholders or a lack of trust in their (economic) sustainability, creating a reinforcing cycle of distrust and limited implementation. This research seeks to break that cycle by proposing a holistic design and optimisation methodology for small-scale biorefineries in Western Europe. The methodology focuses on the three major aspects of any bioproduction process: (i) its supply chain, (ii) its process layout, and (iii) its optimality regarding multiple sustainability indicators. To model the small-scale biorefinery's supply chain, novel GIS methods were developed to assess the availability of kitchen, garden, and agricultural waste using only freely available datasets. Secondly, a customisable process superstructure flowsheet was introduced and simulated with adapted (kinetic) process models from literature, as well as surrogate energy models to account for energy consumption. Finally, custom genetic optimisation algorithms, capable of handling complex black-box multi-objective optimisation problems, were developed and used to optimise the resulting process layout for both profit and energy consumption. These three design and optimisation aspects were combined into one holistic methodology, which was additionally summarised in a proof-of-concept online decision support tool, to guide non-expert users in designing and optimising small-scale biorefineries that meet their requirements. Although initially calibrated for Western Europe, the proposed methodology can be easily adapted to diverse geographic contexts with varying feedstock and policy landscapes. By bridging the gap between complex engineering analyses and community-level decision-making, this holistic solution is expected to foster knowledge and trust in small-scale biorefinery systems, facilitating their broader implementation and accelerating the global transition to a circular carbon economy.
Source: Lirias
Author: De Buck, Viviane
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7113003635
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