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BioTOOL—a Readily and Flexible Biogas Rate Prediction Tool for End-users

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Abstract

This study illustrates an approach to provide an easily manageable tool for end-users to predict the biogas production rate to ease the transition to a flexible and proactive operation of digesters at both biogas plants as well as at wastewater treatment plants. To provide a high flexibility to end-users but keep BioTOOL easily manageable, the approach uses a pre-trained artificial neural networks library consisting of different variable combinations. In BioTOOL’s workflow, end-user will be asked for current measurements disregarding the combination of those. BioTOOL uses a seek-and-implement method to find the correct stored network for the entered input. This approach results in predictions similar to the optimized pre-trained network. It has been demonstrated that the idea of a flexible prediction tool could be fully realized.

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Acknowledgements

This research was supported by the University of Luxembourg as Internal Research Project “BioVirt - Network controlled integration of Biological Wastewater Treatment Plants and Biogas Plants in the concept of Virtual Power Plants.”

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Authors and Affiliations

  1. Chair of Urban Water Management and Hydraulic Engineering, University of Luxembourg, 6, rue Richard Coudenhove-Kalergi, L-1359, Luxembourg, Luxembourg

    Sebastian Hien & Joachim Hansen

  2. Chair of Urban Water Systems Engineering, Technical University of Munich, Am Coulombwall 3, 85748, Garching, Germany

    Jörg E. Drewes & Konrad Koch

Authors
  1. Sebastian Hien
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  2. Joachim Hansen
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  3. Jörg E. Drewes
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  4. Konrad Koch
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Correspondence to Sebastian Hien.

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Hien, S., Hansen, J., Drewes, J.E. et al. BioTOOL—a Readily and Flexible Biogas Rate Prediction Tool for End-users. Environ Model Assess 24, 87–94 (2019). https://doi.org/10.1007/s10666-018-9609-3

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  • DOI: https://doi.org/10.1007/s10666-018-9609-3

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