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Simulation and optimization methods for maximizing biogas production in an anaerobic digestion process

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  • KeChrist Obileke
  • Patrick Mukumba

Abstract

Previous studies on the simulation and optimization of anaerobic digestion have mainly focused on experimental works. However, a review where these studies are synthesized into a cohesive summary published in a single paper is imperative. The review aims to provide recent ways of simulating and optimizing anaerobic digesters, thereby maximizing their biogas yield with the use of software tools. It addresses and provides an overview of the description and development of the process model, optimization techniques associated with biomass feedstock, mathematical model, and standard software used for process simulation. From the review, it is established that methane and carbon dioxide are the critical factors in determining the best optimum substrate ratio in an anaerobic digester. Also, the simulation of anaerobic co-digestion from the study is known to have a higher biogas yield than mono-digestion. The review reported that the stoichiometric method via path degradation is one way of building process simulation. Findings from the review reveal that the significant key optimization parameters are the predictors used for the development of the model, which are usually factors that affect anaerobic digestion. Hence, Aspen Plus, SuperPro Designer, and Response Surface Methodology are regarded as the most effective simulation software tools and optimization techniques employed for anaerobic digestion, respectively. This review article concludes by providing valuable insight into the recommendations, limitations of the study, and suggestions for future studies.

Suggested Citation

  • KeChrist Obileke & Patrick Mukumba, 2025. "Simulation and optimization methods for maximizing biogas production in an anaerobic digestion process," International Journal of Innovative Research and Scientific Studies, Innovative Research Publishing, vol. 8(2), pages 2152-2170.
  • Handle: RePEc:aac:ijirss:v:8:y:2025:i:2:p:2152-2170:id:5644
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