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

  • Sebastian Hien
  • Joachim Hansen
  • Jörg E. Drewes
  • Konrad Koch
Article
  • 47 Downloads

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.

Keywords

Biogas prediction tool Power generation prediction Artificial neural network Wastewater treatment 

Notes

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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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Chair of Urban Water Management and Hydraulic EngineeringUniversity of LuxembourgLuxembourgLuxembourg
  2. 2.Chair of Urban Water Systems EngineeringTechnical University of MunichGarchingGermany

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