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Optimised blending for anaerobic co-digestion using ant colony approach: Besòs river basin case study

Author

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  • Palma-Heredia, D.
  • Verdaguer, M.
  • Molinos-Senante, M.
  • Poch, M.
  • Cugueró-Escofet, M.À.

Abstract

Co-digestion is a well-established strategy to maximise the capacity of anaerobic digestion in wastewater treatment plants (WWTPs). Many tools have been developed to optimise the blend composition. However, the logistics associated with each component of the blend remain a relatively unexplored field, which can yield significant planning challenges. In this paper, an ant colony optimisation based approach is proposed to address these challenges. The proposed algorithm maximises an objective function composed of a first term related to the quality of the sludge and a second term related to the distance between the sludge generator and the anaerobic co-digester. The algorithm successfully optimises the blend composition by considering the related logistics, achieving an optimum blend with an approximately 18% volume of co-substrate. The approach presented here has been used to plan co-digestion using real data from an actual sanitation network composed of 13 WWTPs in the area of the Besòs river basin in Catalonia, and an optimised co-digestion planning strategy with a waste management cost reduction of 77% was obtained.

Suggested Citation

  • Palma-Heredia, D. & Verdaguer, M. & Molinos-Senante, M. & Poch, M. & Cugueró-Escofet, M.À., 2021. "Optimised blending for anaerobic co-digestion using ant colony approach: Besòs river basin case study," Renewable Energy, Elsevier, vol. 168(C), pages 141-150.
    • Handle: RePEc:eee:renene:v:168:y:2021:i:c:p:141-150
    DOI: 10.1016/j.renene.2020.12.064
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    1. Wang, Yihan & Zhang, Lanxin & Wen, Zongguo & Chen, Chen & Cao, Xin & Doh Dinga, Christian, 2023. "Optimization of the sustainable production pathways under multiple industries and objectives: A study of China's three energy- and emission-intensive industries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).

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