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Start-up of multi-species anaerobic digestion systems: extrapolation of the single species approach

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  • M. Sbarciog
  • A. Vande Wouwer

Abstract

This paper presents a brief evaluation of a start-up strategy for multi-species anaerobic digestion systems modelled as two-step reaction systems, where acidogenesis is described by Monod kinetics while the methanogenesis is described by Haldane kinetics. The start-up policy has been developed originally for single species systems with the aim of maximizing the biogas outflow rate. It consists of switching the dilution rate from minimum to maximum and then to the optimal value (bang-bang control) in order to bring the system from an arbitrary initial condition to the optimal set-point. This start-up strategy is applied to the multi-species system using an averaged model, which is usually the only model that can be identified for a multi-species system, as measuring individual biomasses is almost impossible in practice. Even the development of an accurate averaged model, fully characterizing the system dynamics based on the variation of the species proportions is difficult. The averaged models used in this study are built based on a more or less accurate knowledge of the species proportions and their kinetics at the start-up instant and used as such in the application of the start-up policy. It is shown that the start-up policy leads to an efficient ecosystem, characterized by high outflow rate of biogas, which is very close to the maximum even in the case of an inaccurate averaged model. The influence of the model accuracy on the system stability and its productivity is discussed. This study can also be viewed as a robustness evaluation with respect to model inaccuracy of the single species start-up strategy, as the process changes from the averaged kinetics to the kinetics of the winning species during species selection.

Suggested Citation

  • M. Sbarciog & A. Vande Wouwer, 2014. "Start-up of multi-species anaerobic digestion systems: extrapolation of the single species approach," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 20(1), pages 87-104, January.
  • Handle: RePEc:taf:nmcmxx:v:20:y:2014:i:1:p:87-104
    DOI: 10.1080/13873954.2013.817443
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