Next generation surveillance of biogas plants using AI – for improved efficiency and resource utlisation

Increased biogas production, e.g. more biogas plants as well as increased production efficiency per plant, is clearly an important approach to reach Sweden’s environmental and climate targets and a fossil free transport sector.

In this context, a microbiological surveillance has immense potential in management and optimisation of biogas processes, coupled with traditional process monitoring parameters. Our recent previously developed novel model for surveillance of biogas plants shows promising results for indicating process imbalance and can represent a valuable tool for process operation.

To reach the stage of application we propose that this method should be further developed and refined by using extensive long-term surveillance of different types of biogas plants. Data from such surveillance will further be used to develop

  1. deep machine-learning models, to be used for the early warning of process instability, and
  2. rapid on-site community profiling assay.

Anna Schnürer

Swedish University of Agricultural Sciences (SLU)

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Project information


Gasum AB
HZI Jönköping Biogas AB
Scandinavian Biogas Fuels AB
St1 Sverige AB
Uppsala Vatten och Avfall AB
Tekniska verken i Linköping AB
Örebro University

Time schedule

January 2023 - December 2025

Total cost of project

7 459 245 SEK

Swedish Energy Agency project number