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  4. A Method for Determining the Market Potential of Biogas Plants in Cross-industrial Systems using Ant Colony Optimization
 
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2025
Conference Paper
Title

A Method for Determining the Market Potential of Biogas Plants in Cross-industrial Systems using Ant Colony Optimization

Abstract
The end of EEG subsidies has left many biogas plants in Germany facing economic challenges. This study examines how biogas plants can develop new business models by integrating them into cross-industrial systems as part of industrial symbiosis. These systems link actors across sectors through the use of renewable energies and Power-to-X technologies to make use of excess carbon. This is demonstrated through the example of the methanol synthesis to methanol-to-olefins process and the utilisation of biomethane materials using a numerical algorithm. The algorithm combines ant colony optimisation and the multi-criteria evaluation method Promethee-II to identify georeferenced network potential. The analysis of the Hünxe region in Germany shows that relevant networks can be created by linking biogas plants with nearby industrial players. These networks demonstrate clustering of methane flows and competitive behaviour between biogenic and locally produced fossil CO₂. The results demonstrate that targeted transformation pathways and political incentives are necessary to enable the long-term use of biogenic CO₂ and create new sales opportunities for biogas plants. This study provides a methodological framework for dentifying and evaluating cross-industrial system structures for regional defossilisation.
Author(s)
Heil, Jonathan Tobias  orcid-logo
Fraunhofer-Institut für Umwelt-, Sicherheits- und Energietechnik UMSICHT  
Mainwork
33rd European Biomass Conference and Exhibition 2025. Proceedings  
Conference
European Biomass Conference and Exhibition 2025  
DOI
10.5071/33rdEUBCE2025-2BV.7.11
Language
English
Fraunhofer-Institut für Umwelt-, Sicherheits- und Energietechnik UMSICHT  
Keyword(s)
  • circular economy

  • CO2 capture

  • market

  • methanol

  • model

  • supply chain

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