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Optimization of hydrogen production in anaerobic digesters with input and state estimation and model predictive control

Abstract : This paper addresses the problem of optimization of hydrogen production in continuous anaerobic digesters utilizing an model predictive control (MPC) strategy. The process is described by a dynamic nonlinear model. The influent COD concentration together with the effluent substrate and product concentrations are considered as state variables and estimated by an asymptotic online observer from measurements of gas composition and gas flow rate. It is experimentally demonstrated that a 75% increase of the hydrogen production can be obtained using the influent flow rate as the main control variable while keeping the conversion of the influent COD concentration higher than 95 %.
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https://hal.inrae.fr/hal-02659193
Déposant : Migration Prodinra <>
Soumis le : samedi 30 mai 2020 - 13:40:03
Dernière modification le : vendredi 5 février 2021 - 04:03:01

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  • HAL Id : hal-02659193, version 1
  • PRODINRA : 27811

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Cesar Arturo Aceves-Lara, Eric Latrille, Nicolas Bernet, Pierre Buffière, Jean-Philippe Steyer. Optimization of hydrogen production in anaerobic digesters with input and state estimation and model predictive control. e-STA Sciences et Technologies de l’Automatique, SEE - Société de l'Electricité, de l'Electronique et des Technologies de l'Information et de la Communication 2008, 5 (2), s.p. ⟨hal-02659193⟩

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